Bayesian interpretation to generalize adaptive mean shift algorithm
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[1] Hui Xiong,et al. Understanding of Internal Clustering Validation Measures , 2010, 2010 IEEE International Conference on Data Mining.
[2] Artur Chodorowski,et al. A fully automatic unsupervised segmentation framework for the brain tissues in MR images , 2014, Medical Imaging.
[3] Trevor Darrell,et al. Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (Neural Information Processing) , 2006 .
[4] Keinosuke Fukunaga,et al. Introduction to Statistical Pattern Recognition , 1972 .
[5] Larry D. Hostetler,et al. The estimation of the gradient of a density function, with applications in pattern recognition , 1975, IEEE Trans. Inf. Theory.
[6] Dimitri P. Bertsekas,et al. Nonlinear Programming , 1997 .
[7] Anton van den Hengel,et al. Fast Global Kernel Density Mode Seeking: Applications to Localization and Tracking , 2007, IEEE Transactions on Image Processing.
[8] David J. Kriegman,et al. From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[9] D. W. Scott,et al. Multivariate Density Estimation, Theory, Practice and Visualization , 1992 .
[10] Markus Breitenbach,et al. Clustering through ranking on manifolds , 2005, ICML '05.
[11] C. D. Kemp,et al. Density Estimation for Statistics and Data Analysis , 1987 .
[12] Mikael Persson,et al. A novel Bayesian approach to adaptive mean shift segmentation of brain images , 2012, 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS).
[13] Carlotta Domeniconi,et al. A Weighted Adaptive Mean Shift Clustering Algorithm , 2014, SDM.
[14] Gary Bradski,et al. Computer Vision Face Tracking For Use in a Perceptual User Interface , 1998 .
[15] G. Casella,et al. Rao-Blackwellisation of sampling schemes , 1996 .
[16] David W. Scott,et al. Multivariate Density Estimation: Theory, Practice, and Visualization , 1992, Wiley Series in Probability and Statistics.
[17] Julio Gonzalo,et al. A comparison of extrinsic clustering evaluation metrics based on formal constraints , 2008, Information Retrieval.
[18] Simon P. Wilson,et al. Mean Shift Algorithm with Heterogeneous Node Weights ∗ , 2010 .
[19] Dorin Comaniciu,et al. Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[20] Ilan Shimshoni,et al. Mean shift based clustering in high dimensions: a texture classification example , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[21] Francesco Calabrese,et al. Time of arrival predictability horizons for public bus routes , 2011, CTS '11.
[22] Dorin Comaniciu,et al. The Variable Bandwidth Mean Shift and Data-Driven Scale Selection , 2001, ICCV.
[23] Jun S. Liu,et al. Monte Carlo strategies in scientific computing , 2001 .
[24] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[25] Nando de Freitas,et al. An Introduction to MCMC for Machine Learning , 2004, Machine Learning.
[26] M. C. Jones,et al. A Brief Survey of Bandwidth Selection for Density Estimation , 1996 .